Identification and extraction of characterized information from complex high-dimensional biological data is a very meaningful issue. The dimensionality reduction fusion method based on random forest, feature extraction and neural network is proposed to recognize and classify two datasets of mRNA and lncRNA. It is shown that the proposed fusion method achieved accurate identification/classification of cancer and non-cancer groups, and simultaneously selected identity variables that have biological relevance to lung cancer (tumor) as potential biomarkers from a large number of variables. It is considered as an effective tool and theoretical support for lung cancer identification in clinical application, and it can be extended to other kinds of cancer or biological data. Ultimately, an advanced method for feature extraction and classification analysis of high-dimensional data is provided.

Assessment of the level of contamination from possible impact of spent crankcase oil on soil ecosystem is imperative for the determination of environmental acceptability. This study investigated this impact ex-situ using a culture-dependent approach to evaluate the total microbial counts; biochemical and physicochemical tools to determine the activities of their exudates (acid and alkaline phosphatases), total petroleum hydrocarbon (TPH) and pH as indices. The experiment demonstrated that at 1.5 – 3.5% contamination across days-zero to -28, spent crankcase oil stimulated significantly (p<0.05) the activity of alkaline phosphatase in a concentration and time dependent manner from 4.0 ± 0.03 to 8.0 ± 0.00Katal. Acid phosphatase suffered inhibition significantly (p<0.05) from 6.0 ± 0.05 to 2.8 ± 0.01Katal. The contamination significantly (p<0.05) increased the total petroleum hydrocarbon (TPH) across all the days relative to control and this lowered the pH from 5.9 ± 0.00 to 4.8 ± 0.00. An initial reduction in microbial biomass from 1.32 x 109 ± 0.00 to 3.48 x108 ± 0.00 cfu/g on week one, and induction of hydrocarbon-degrading organisms, (the hydrocarbonclastics), to 3.7 x 10¬¬8 ± 0.10cfu/g at 1.5 – 3.5% contamination overtime correlated with enzyme induction, and activity. Ecosystem dynamics and mineralization were impaired and disrupted and the entire soil biochemistry was altered.

Poly-aromatic hydrocarbon (PAH) effluents arising from vehicular spent petroleum products on highways were assessed. Analysis of this impact on cassava leaves and tubers on highway using the method of AOAC, 1990 revealed xylene to be of highest concentration, 0.1449 and 0.1865mm/g in leaves and roots respectively. Other PAHs analyzed were found to contain as follows: acenapthylene (0.0003 and 0.0312mm/g), phenanthlene (0.0029 and 0.0003mm/g), anthracene (0.0067 and 0.0127mm/g), 1,2-benzathracene (0.0161 and 0.0126mm/g), benzo(k)fluorine (0.0001 and 0.223mm/g) and pyrene (0.0169 and 0.0329mm/g) for leaves and roots respectively. From these findings, the concentration of PAH is highest in cassava roots than leaves and this justifies its hazardous effects on humans. Therefore, environmental monitoring of poly aromatic hydrocarbons in food is imperative in evaluating the possible toxicity of the impact as well as the carcinogenic potential of these compounds to humans via intake.

Polyphenolic phytochemicals of Cola nitida, with their potential therapeutic ability can modulate metabolic and transcriptional expression of proteins and enzymatic activities that culminate to hyperglyceamic effects. This study investigated the hyperglyceamic effects of polyphenolic phytochemical extracts of Cola nitida in Wistar rat in-vivo and established a parallel inhibition of the enzymes (α-amylase and α-glucosidase) in their activities as the concentration increased. On administration of the extracts, the activity of α-amylase was inhibited from control, 32 ± 0.00 to 16 ± 0.02u/L as the concentration increased. Also, the activity of α- glucosidase was inhibited from 17 ± 0.01 to 10 ± 0.00u/L in relation to the concentration of the extracts. The inhibitory effect of Cola nitida on carbohydrate hydrolyzing enzymes delayed glucose utilization resulting to elevated glucose concentration from 6.07 ± 0.02 to 9.11 ± 0.01 mMol/L. The composition of the polyphenolic phytochemicals in the Cola nitida analyzed with gas chromatographic techniques was found to contain; apigenin, 6.0 ± 0.01; catechin, 7.1± 0.01; epicatechin, 4.8 ± 0.02; narigenin, 4.9 ± 0.10 mg/100mg and these are the active ingredients of the bioactive compounds that are responsible for the hyperglyceamic effects of Cola nitida.